Publication Harvesting Randomness to Optimize Distributed Systems Mathias Lecuyer, Joshua Lockerman, Lamont Nelson, Siddhartha Sen, Amit Sharma, Aleksandrs Slivkins 16th ACM Workshop on Hot Topics in Networks (HotNets) | November 2017
Publication Oracle-Efficient Learning and Auction Design Miro Dudík, Nika Haghtalab, Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, Jennifer Wortman Vaughan Proceedings of the 58th Annual Symposium on Foundations of Computer Science (FOCS), 2017. | October 2017
Publication Contextual Decision Processes with low Bellman rank are PAC-Learnable Nan Jiang, Akshay Krishnamurthy, Alekh Agarwal, John Langford, Robert E. Schapire International Conference on Machine Learning | August 2017 Project
Publication Optimal and Adaptive Off-policy Evaluation in Contextual Bandits Yu-Xiang Wang, Alekh Agarwal, Miro Dudík The 34th International Conference on Machine Learning (ICML 2017) | August 2017
Publication An online hierarchical algorithm for extreme clustering Ari Kobren, Akshay Krishnamurthy, Nicholas Monath, Andrew McCallum Knowledge Discovery and Data Mining | August 2017
Publication Mapping Instructions and Visual Observations to Actions with Reinforcement Learning Dipendra Misra, John Langford, Yoav Artzi July 2017 Project
Publication Hyperbolic Caching: Flexible Caching for Web Applications Aaron Blankstein, Siddhartha Sen, Michael J. Freedman USENIX Annual Technical Conference (ATC) | July 2017
Publication Corralling a Band of Bandit Algorithms Alekh Agarwal, Haipeng Luo, Behnam Neyshabur, Robert E. Schapire Proceedings of the 2017 Conference on Learning Theory (COLT) | July 2017
Publication Open Problem: First-Order Regret Bounds for Contextual Bandits Alekh Agarwal, Akshay Krishnamurthy, John Langford, Haipeng Luo, Robert E. Schapire Conference on Learning Theory | July 2017
Publication Surge Pricing Solves the Wild Goose Chase Juan Camilo Castillo, Dan Knoepfle EC ’17 Proceedings of the 2017 ACM Conference on Economics and Computation | June 2017
